Abstract
Rate-distortion optimization (RDO) plays an essential role in substantially enhancing the coding efficiency. Currently, rate-distortion optimized mode decision is widely used in scalable video coding (SVC). Among all the possible coding modes, it aims to select the one which has the best trade-off between bitrate and compression distortion. Specifically, this tradeoff is tuned through the choice of the Lagrange multiplier. Despite the prevalence of conventional method for Lagrange multiplier selection in hybrid video coding, the underlying formulation is not applicable to 3-D wavelet-based SVC where the explicit values of the quantization step are not available, with on consideration of the content features of input signal. In this paper, an efficient content adaptive Lagrange multiplier selection algorithm is proposed in the context of RDO for 3-D wavelet-based SVC targeting quality scalability. Our contributions are two-fold. First, we introduce a novel weighting method, which takes account of the mutual information, gradient per pixel, and texture homogeneity to measure the temporal subband characteristics after applying the motion-compensated temporal filtering (MCTF) technique. Second, based on the proposed subband weighting factor model, we derive the optimal Lagrange multiplier. Experimental results demonstrate that the proposed algorithm enables more satisfactory video quality with negligible additional computational complexity.
Highlights
With the rapid development of video services in recent years, how to efficiently compress video sequences has been considered as a very challenging task for transmitting video data over heterogeneous networks
Owing to the intrinsic localization and multiresolution features of the discrete wavelet transform (DWT), video codecs based on motion-compensated three-dimensional (3-D) DWT have been studied extensively for use in scalable video coding (SVC) [5,6,7,8]. 3-D wavelet-based SVC provides a natural way in producing embedded bitstreams with full scalability and fine granularity for in-network adaptation [9,10]
Extensive experiments have been conducted to verify the effectiveness of the proposed content adaptive Lagrange multiplier selection algorithm for 3-D wavelet-based SVC
Summary
With the rapid development of video services in recent years, how to efficiently compress video sequences has been considered as a very challenging task for transmitting video data over heterogeneous networks. In the 3-D wavelet-based SVC, temporal redundancy across frames is exploited by adopting the motion-compensated temporal filtering (MCTF) framework [11,12,13,14], and spatial redundancy inside a frame is utilized by 2-D spatial transform. Such codecs do not suffer from the drift problem often
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